Volume 56

Intelligent Optimization Method for CCUS Injection Parameters Based on Improved NSGA-II Algorithm Honghong Li, Yanan Zhang, Bing Chen, Songyan Sang, Hongzhi Han, Miao Liu

Abstract

In CO2 enhanced oil recovery (EOR) and sequestration operations, the temperature and pressure of bottomhole fluids play a crucial role in determining CO2’s oil solubility and mobility. To achieve optimal EOR and sequestration results, it is essential to design parameters such as injection temperature, pressure, wellbore structure, and insulation materials. To address the issues in designing CCUS injection parameters, this paper proposes a multi-objective intelligent optimization method for CCUS injection parameters based on an improved second-generation Non-dominated Sorting Genetic Algorithm (NSGA-II). First, a CO2 injection wellbore temperature and pressure calculation model is constructed, enabling the characterization of fluid flow along the wellbore and the simulation of bottomhole temperature and pressure. Subsequently, by introducing an Estimation of Distribution Algorithm (EDA), the randomness and lack of purpose in the crossover and mutation operations of the traditional NSGA-II algorithm are mitigated, thereby enhancing the optimization performance and convergence speed of the algorithm. Finally, through case analysis, the effectiveness and superiority of this intelligent optimization method in designing CCUS injection parameters are validated.

Keywords CCUS, Injection Well, NSGA-II Algorithm, Estimation of Distribution Algorithm